Can Modern Statistical Parsers Lead to Better Natural Language Understanding for Education?

摘要

We use state-of-the-art parsing technology to build GeoSynth - a system that can automatically solve word problems in geometric constructions. Through our experiments we show that even though off-the-shelf parsers perform poorly on texts containing specialized vocabulary and long sentences, appropriate preprocessing of text before applying the parser and use of extensive domain knowledge while interpreting the parse tree can together help us circumvent parser errors and build robust domain specific natural language understanding modules useful for various educational applications.